Job description

YOU ARE GOING TO:

  • Work with us at the forefront of the digital revolution contributing your creativity, innovativeness, critical thinking and numeric skills to help us shape the global digital landscape.

  • Use machine learning and cloud technologies to improve Client businesses by enabling data science capabilities at scale.

  • Work in interdisciplinary teams that gather technical, business, cloud and data science competencies that deliver work in agile methodologies (at client localisation, remotely or mixed).

  • The range of your accountability, responsibility and autonomy will depend on your experience and seniority - we are looking for specialists with various experience levels.

  • Have minimum Bachelor's degree in discipline like Informatics, Physics, Mathematics, Quantitative Methods and are continuously looking forward to using your knowledge to solve complex business problems.

  • Have at least 1-2 years of practical experience within industry or consulting in applying data-driven approaches to a variety of business scenarios, including creation and use of advanced analytics / Machine Learning algorithms. Retail or FMCG experience will be an asset.

  • Are proficient in at least one of programming and query languages like Python, PySpark, SQL.

  • Understand various Data Science and Machine Learning concepts and algorithms such as clustering, regression, classification, forecasting, neural networks, hyperparameters optimization, NLP.

  • Have an unstoppable thirst for knowledge and are comfortable with ongoing skills development whether it comes to learning completely new technology or mastering relevant ML algorithm.

  • Understand that Data Engineering is one of the key components of successful delivery in Analytics and are capable of working at any step of analytical model development.

  • Have experience or interest in delivering analytical projects with top Cloud platforms such as GCP, Azure, AWS. Experience with Databricks, BigQuery or AirFlow will be an asset.

  • You understand ML model lifecycle. Practical experience with containerization tools such as Docker, Kubernetes and model lineage tools such as MLflow would be an asset.

  • Have a very good command of English language (it is nice to have command of additional language, for instance, German).

  • Are a great team player (it is nice to have experience in working in international teams).

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